Suchergebnisse

[ES] This data-paper presents and describes a consolidated, harmonized, internationally comparable database to quantify the impacts of the housing affordability crisis. Local harmonized indicators allow to examine the unequal spatial patterns of housing affordability across a selection of European cities. This study seeks at informing and mapping the increased and unequal affordability gap, a critical issue for social cohesion and sustainability in metropolitan areas in Europe. We characterize affordability with measures of price (property and rent) and income in a selection of European Functional Urban Areas (FUAs). The methodological goal was to cope with a data gap, i.e. a lack of harmonized spatial data to map and analyze affordability in Europe. This research, conducted in 2018-19 by a European consortium for the ESPON agency, covers 4 countries and one cross-border region: Geneva (Switzerland), Annecy-Annemasse, Avignon and Paris (France), Madrid, Barcelona and Palma de Majorca (Spain) and Warsaw, Łódź and Krakow (Poland). We bring insights on how institutional data (i.e. transactions data), can be bridged with unconventional data ("big data" harvested on line) to provide a cost-effective and harmonized data collection effort that can contribute to compare affordability within cities (between neighborhoods) and across cities, using various geographical levels (1km square-grid, municipalities, FUA). We present the structure of the database, how it has been constructed in a reproducible manner; we document the validation process, the strengths and limitations of the data provided, and document the reproducibility of the workflow. ; [FR] Cet article présente et décrit une base de données consolidée, harmonisée et comparable au niveau international pour quantifier les impacts de la crise de l'accessibilité (ou abordabilité) du logement. Cette base de données permet de caractériser l'inégale abordabilité du logement dans une sélection de métropoles européennes, une question cruciale pour la cohésion sociale et la durabilité dans les zones métropolitaines en Europe. La question porte sur l'inégalité d'accès au logement, en fonction des revenus. Mais cet écart s'est creusé au cours des dernières décennies : depuis les années 1990, les prix des logements ont en moyenne augmenté plus vite que les revenus des résidents et des acheteurs. La base de données caractérise l'abordabilité à l'aide de mesures du prix (propriété et loyer) et du revenu dans une sélection de zones urbaines fonctionnelles européennes (Functional Urban Areas, FUA). L'objectif méthodologique est de combler une lacune, c'est-à-dire l'absence de données spatiales harmonisées pour cartographier et analyser l'accessibilité financière en Europe. Cette étude, menée en 2018-19 par un consortium européen pour ESPON, couvre 4 pays de la zone et une région transfrontalière : Genève (Suisse), Annecy-Annemasse, Avignon et Paris (France), Madrid, Barcelone et Palma de Majorque (Espagne) et Varsovie, Łódź et Cracovie (Pologne). Nous apportons un éclairage sur la manière dont les données institutionnelles (données sur les transactions) peuvent être rapprochées des données collectées en ligne, et harmonisées pour contribuer à comparer l'accessibilité financière au sein des villes (entre les quartiers) et entre les villes, en utilisant différents niveaux géographiques (grille carroyée de 1 km, municipalités, FUA). Nous présentons la structure de la base de données, comment elle a été construite de manière reproductible ; nous documentons le processus de validation, les forces et les limites des données fournies, et documentons la reproductibilité de l'analyse. ; [ES] Este artículo presenta y describe una base de datos consolidada, armonizada e internacionalmente comparable para cuantificar los impactos de la crisis de acceso a la vivienda, un tema crucial para la cohesión social y sostenibilidad en las áreas metropolitanas de Europa. La base de datos caracteriza tal proceso en una muestra de las metrópolis europeas, abordando la interrogante sobre la desigualdad en el acceso a la vivienda en función de los ingresos, brecha que se ha visto incrementada en las últimas décadas. Desde los años 1990, los precios de la vivienda en promedio han aumentado más rápido que los ingresos de residentes y compradores. La base de datos caracteriza el acceso utilizando medidas de precio (propiedad y arriendo) e ingresos en una selección de áreas urbanas funcionales europeas (FUA). El objetivo metodológico es contribuir al vacío y falta de datos espaciales armonizados para cartografiar y analizar la accesibilidad financiera en Europa. Este estudio, realizado en 2018-19 por un consorcio europeo para ESPON, cubre 4 países de la zona y una región transfronteriza: Ginebra (Suiza); Annecy-Annemasse, Aviñón y París (Francia); Madrid, Barcelona y Palma de Mallorca (España); Varsovia, Lodz y Cracovia (Polonia). El trabajo aporta cómo los datos institucionales (datos en las transacciones) pueden vincularse con los datos recopilados en línea y armonizar una base para contribuir a comparar la accesibilidad financiera al interior de las ciudades (entre barrios) y entre ciudades, utilizando diferentes escalas geográficas (cuadrícula de 1 km, municipios, FUA). Presentamos y documentamos la estructura de la base de datos, su elaboración y validación, las fortalezas y limitaciones de los datos proporcionados, y la reproducibilidad del análisis. ; The transactions BIEN proprietary database was made available by Paris Notaire Service, on the behalf of the Chamber of the Notaries, under an agreement contracted by the LabEx DynamiTe (ANR-11-LABX-0046) consortium and the Univ. Paris 1 Pantheon-Sorbonne. Data provided by the INSEE (1 km grid) contains public sector information, made available under ©INSEE, 2013. Mattia Mazzoli is funded by the Conselleria d'Innovació, Recerca i Turisme of the Government of the Balearic Islands and the European Social Fund with grant code FPI/2090/2018. J.J.R., M.M. and P.C. also acknowledge funding from the Spanish Ministry of Science and Innovation, the AEI and FEDER (EU) under the grant PACSS (RTI2018-093732-B-C22) and the Maria de Maeztu program for Units of Excellence in R&D (MDM-2017-0711). ; Peer reviewed

The gathering and harmonisation of international statistical data in a multidisciplinary environment are key to international comparative analysis and policy work. The availability of timely, accurate statistical information enables policy-makers, practitioners, researchers and other stakeholders to address a wide range of issues in today's rapidly-evolving global economic and social landscape.The use of traditional data such as official administrative statistics however has some shortcomings. Traditional data in general takes long to be published and used because they are subject to a long technical and sometimes political process of harmonization and validation. Also, traditional data does not cover all topics of interest for territorial cohesion.Increasingly, data and information from analysing internet activities or social media can be used for observing territorial development trends. New developments for the availability and use of big data may help to overcome the shortcomings and bring new and interesting opportunities to support policy with up-to-date information relevant for territorial analysis.Currently, the interest from policy makers is growing as the sources for Big Data (Facebook, Google, Twitter, Instagram or blogs for example) contain valuable information, which can normally be hard to gather, and these data can be collected with very short notice. This means that Big Data could provide a more regular, cost-effective and harmonised data collection and provide an opportunity to more easily address new issues of interest.The aim of this ESPON activity is to further develop ways and methodologies for using existing big data sources and platforms to develop and measure indicators for territorial monitoring and analysis. In addition, these methodologies should be applied for indicators measuring the housing dynamics in European cities and the wellbeing of European citizens, in particular related to their housing and living situation. Finally, these methodologies should be made available and applicable to others for measuring these and other aspects in cities.

The gathering and harmonisation of international statistical data in a multidisciplinary environment are key to international comparative analysis and policy work. The availability of timely, accurate statistical information enables policy-makers, practitioners, researchers and other stakeholders to address a wide range of issues in today's rapidly-evolving global economic and social landscape.The use of traditional data such as official administrative statistics however has some shortcomings. Traditional data in general takes long to be published and used because they are subject to a long technical and sometimes political process of harmonization and validation. Also, traditional data does not cover all topics of interest for territorial cohesion.Increasingly, data and information from analysing internet activities or social media can be used for observing territorial development trends. New developments for the availability and use of big data may help to overcome the shortcomings and bring new and interesting opportunities to support policy with up-to-date information relevant for territorial analysis.Currently, the interest from policy makers is growing as the sources for Big Data (Facebook, Google, Twitter, Instagram or blogs for example) contain valuable information, which can normally be hard to gather, and these data can be collected with very short notice. This means that Big Data could provide a more regular, cost-effective and harmonised data collection and provide an opportunity to more easily address new issues of interest.The aim of this ESPON activity is to further develop ways and methodologies for using existing big data sources and platforms to develop and measure indicators for territorial monitoring and analysis. In addition, these methodologies should be applied for indicators measuring the housing dynamics in European cities and the wellbeing of European citizens, in particular related to their housing and living situation. Finally, these methodologies should be made available and applicable to others for measuring these and other aspects in cities.

The gathering and harmonisation of international statistical data in a multidisciplinary environment are key to international comparative analysis and policy work. The availability of timely, accurate statistical information enables policy-makers, practitioners, researchers and other stakeholders to address a wide range of issues in today's rapidly-evolving global economic and social landscape.The use of traditional data such as official administrative statistics however has some shortcomings. Traditional data in general takes long to be published and used because they are subject to a long technical and sometimes political process of harmonization and validation. Also, traditional data does not cover all topics of interest for territorial cohesion.Increasingly, data and information from analysing internet activities or social media can be used for observing territorial development trends. New developments for the availability and use of big data may help to overcome the shortcomings and bring new and interesting opportunities to support policy with up-to-date information relevant for territorial analysis.Currently, the interest from policy makers is growing as the sources for Big Data (Facebook, Google, Twitter, Instagram or blogs for example) contain valuable information, which can normally be hard to gather, and these data can be collected with very short notice. This means that Big Data could provide a more regular, cost-effective and harmonised data collection and provide an opportunity to more easily address new issues of interest.The aim of this ESPON activity is to further develop ways and methodologies for using existing big data sources and platforms to develop and measure indicators for territorial monitoring and analysis. In addition, these methodologies should be applied for indicators measuring the housing dynamics in European cities and the wellbeing of European citizens, in particular related to their housing and living situation. Finally, these methodologies should be made available and ...

The gathering and harmonisation of international statistical data in a multidisciplinary environment are key to international comparative analysis and policy work. The availability of timely, accurate statistical information enables policy-makers, practitioners, researchers and other stakeholders to address a wide range of issues in today's rapidly-evolving global economic and social landscape.The use of traditional data such as official administrative statistics however has some shortcomings. Traditional data in general takes long to be published and used because they are subject to a long technical and sometimes political process of harmonization and validation. Also, traditional data does not cover all topics of interest for territorial cohesion.Increasingly, data and information from analysing internet activities or social media can be used for observing territorial development trends. New developments for the availability and use of big data may help to overcome the shortcomings and bring new and interesting opportunities to support policy with up-to-date information relevant for territorial analysis.Currently, the interest from policy makers is growing as the sources for Big Data (Facebook, Google, Twitter, Instagram or blogs for example) contain valuable information, which can normally be hard to gather, and these data can be collected with very short notice. This means that Big Data could provide a more regular, cost-effective and harmonised data collection and provide an opportunity to more easily address new issues of interest.The aim of this ESPON activity is to further develop ways and methodologies for using existing big data sources and platforms to develop and measure indicators for territorial monitoring and analysis. In addition, these methodologies should be applied for indicators measuring the housing dynamics in European cities and the wellbeing of European citizens, in particular related to their housing and living situation. Finally, these methodologies should be made available and applicable to others for measuring these and other aspects in cities.

The gathering and harmonisation of international statistical data in a multidisciplinary environment are key to international comparative analysis and policy work. The availability of timely, accurate statistical information enables policy-makers, practitioners, researchers and other stakeholders to address a wide range of issues in today's rapidly-evolving global economic and social landscape.The use of traditional data such as official administrative statistics however has some shortcomings. Traditional data in general takes long to be published and used because they are subject to a long technical and sometimes political process of harmonization and validation. Also, traditional data does not cover all topics of interest for territorial cohesion.Increasingly, data and information from analysing internet activities or social media can be used for observing territorial development trends. New developments for the availability and use of big data may help to overcome the shortcomings and bring new and interesting opportunities to support policy with up-to-date information relevant for territorial analysis.Currently, the interest from policy makers is growing as the sources for Big Data (Facebook, Google, Twitter, Instagram or blogs for example) contain valuable information, which can normally be hard to gather, and these data can be collected with very short notice. This means that Big Data could provide a more regular, cost-effective and harmonised data collection and provide an opportunity to more easily address new issues of interest.The aim of this ESPON activity is to further develop ways and methodologies for using existing big data sources and platforms to develop and measure indicators for territorial monitoring and analysis. In addition, these methodologies should be applied for indicators measuring the housing dynamics in European cities and the wellbeing of European citizens, in particular related to their housing and living situation. Finally, these methodologies should be made available and applicable to others for measuring these and other aspects in cities.

The gathering and harmonisation of international statistical data in a multidisciplinary environment are key to international comparative analysis and policy work. The availability of timely, accurate statistical information enables policy-makers, practitioners, researchers and other stakeholders to address a wide range of issues in today's rapidly-evolving global economic and social landscape.The use of traditional data such as official administrative statistics however has some shortcomings. Traditional data in general takes long to be published and used because they are subject to a long technical and sometimes political process of harmonization and validation. Also, traditional data does not cover all topics of interest for territorial cohesion.Increasingly, data and information from analysing internet activities or social media can be used for observing territorial development trends. New developments for the availability and use of big data may help to overcome the shortcomings and bring new and interesting opportunities to support policy with up-to-date information relevant for territorial analysis.Currently, the interest from policy makers is growing as the sources for Big Data (Facebook, Google, Twitter, Instagram or blogs for example) contain valuable information, which can normally be hard to gather, and these data can be collected with very short notice. This means that Big Data could provide a more regular, cost-effective and harmonised data collection and provide an opportunity to more easily address new issues of interest.The aim of this ESPON activity is to further develop ways and methodologies for using existing big data sources and platforms to develop and measure indicators for territorial monitoring and analysis. In addition, these methodologies should be applied for indicators measuring the housing dynamics in European cities and the wellbeing of European citizens, in particular related to their housing and living situation. Finally, these methodologies should be made available and applicable to others for measuring these and other aspects in cities.